Progress in neural recording is critical to understanding the brain and developing treatments for brain disorders. Current neural recordings can, at best, capture a few hundred interacting neurons. The number of recorded neurons is relatively small because current neural recording devices, such as electrodes, amplifiers, lasers, and cameras, are macroscopic. The objective of our research is to create neural recorders at the molecular scale, by writing neural activities onto DNA, like a molecular ticker tape. The device will consist of an engineered DNAP polymerase that can be cheaply synthesized and easily delivered to neurons, where it will write the temporal dynamics of activity of each neuron onto local DNA molecules, which can later be analyzed via increasingly cheap genome sequencing technologies. The long term goal of our research is to enable a paradigm shift, making recording instrumentation-free, easy to use, and scalable to arbitrary numbers of neurons. We will obtain the nanoscale recording device using three pipelines: (1) Polymerase design pipeline. We will search through different DNA polymerases to find a polymerase that makes many replication mistakes when ion concentrations increase, and thus when neurons are active. We will use directed protein engineering to add ion-sensitive domains. Lastly we will use high throughput protein directed evolution, to produce a polymerase with desirable properties. (2) Template design pipeline. We will design and deliver an engineered DNA template to the cell to be copied. We will utilize transfection, which is feasible but might not be convenient in some neuroscientific experiments, moving later towards viral template delivery methods, which may be simpler. (3) Statistics pipeline. The resulting DNA sequences need to be converted back into signals of neurobiological meaning. Such conversion needs to be precise, robust to various problems such as biological polymerase noise, and error-correcting. The approach is innovative, because it reinvents the concept of recording using molecular engineering to produce a device that is orders of magnitude smaller and arguably more versatile than comparable devices. The proposed research is significant, because it allows a whole range of new electrophysiological experiments. The approach will complement other emerging approaches that promise to lead to large dataset based neuroscience, e.g. connectomics. The resulting technique will be easyto- use and inexpensive, yet will promise to allow recording simultaneously from potentially arbitrary numbers of neurons, with temporal precision comparable to existing state-of-the-art calcium imaging. It promises massively increased amounts of neural data and entirely new approaches to asking deep questions about the way the brain works and how to cure disease of the brain.
The proposed research is relevant to public health because it will result in a tool, a molecular neural activity recorder, that will enable substantial progress n wide areas of neuroscience, both basic and clinical. Hence, the proposed research is relevant to the part of NIH's mission that pertains to foster fundamental creative discoveries, innovative research strategies, and their applications as a basis for ultimately protecting and improving health.
Kolb, Ilya; Talei Franzesi, Giovanni; Wang, Michael et al. (2018) Evidence for Long-Timescale Patterns of Synaptic Inputs in CA1 of Awake Behaving Mice. J Neurosci 38:1821-1834 |
Karagiannis, Emmanouil D; Boyden, Edward S (2018) Expansion microscopy: development and neuroscience applications. Curr Opin Neurobiol 50:56-63 |
Kalhor, Reza; Kalhor, Kian; Mejia, Leo et al. (2018) Developmental barcoding of whole mouse via homing CRISPR. Science 361: |
Piatkevich, Kiryl D; Jung, Erica E; Straub, Christoph et al. (2018) A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters. Nat Chem Biol 14:352-360 |
Oran, Daniel; Rodriques, Samuel G; Gao, Ruixuan et al. (2018) 3D nanofabrication by volumetric deposition and controlled shrinkage of patterned scaffolds. Science 362:1281-1285 |
Nivala, Jeff; Shipman, Seth L; Church, George M (2018) Spontaneous CRISPR loci generation in vivo by non-canonical spacer integration. Nat Microbiol 3:310-318 |
Benjamin, Ari S; Fernandes, Hugo L; Tomlinson, Tucker et al. (2018) Modern Machine Learning as a Benchmark for Fitting Neural Responses. Front Comput Neurosci 12:56 |
Younger, Andrew K D; Su, Peter Y; Shepard, Andrea J et al. (2018) Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion. Protein Eng Des Sel 31:55-63 |
Wu, Jing; de Paz, Alexandra; Zamft, Bradley M et al. (2017) DNA binding strength increases the processivity and activity of a Y-Family DNA polymerase. Sci Rep 7:4756 |
Cybulski, Thaddeus R; Boyden, Edward S; Church, George M et al. (2017) Nucleotide-time alignment for molecular recorders. PLoS Comput Biol 13:e1005483 |
Showing the most recent 10 out of 31 publications